Optical coherence tomography (OCT) is a well-established medical imaging technique used to create three-dimensional (3D) images of, for example, the retina. Analysis of images recorded using OCT can delineate the layers of the retina through a procedure referred to as retinal layer segmentation. Such technologies are used clinically to determine variations in the relative thickness of certain retinal layers, as these thicknesses have been shown to relate to various pathologies. In many cases, a choice of treatment can depend in part on parameters such as retinal layer thicknesses. As the eye is an extension of the central nervous system, technologies associated with the imaging and delineation of retinal layers have medical uses beyond those limited to the detection and management of ocular pathologies.
Advanced stage ocular diseases tend to severely disrupt the normal architecture of the retina, which can increase the likelihood of failure for automated algorithms used for retinal layers segmentation. In such cases, however, the retinal structure and its response to treatment still needs to be accurately assessed. This can require input from an operator, such as a researcher or clinician, to edit pre-existing layer delineations, or to generate entirely new layer delineations. Editing of layers is done based on repeatedly working with two-dimensional (2D) images extracted from the 3D volumes. The efficiency of methods for generating and editing these layer delineations can significantly impact their utility and robustness.